Index Map Research Articles

Abstract 4120577: Discrimination of Fabry Disease and Cardiac Amyloidosis Using Cardiac MRI and Echocardiography: A Comprehensive Analysis

Background: Discriminating Fabry disease from cardiac amyloidosis based on conventional imaging techniques can be challenging due to overlapping features. We aimed to investigate the discriminatory ability of cardiac MRI (CMR) and echocardiography imaging, to differentiate between these conditions. Methods: Cardiac MRI and echocardiography with SR imaging were performed on patients with suspected Fabry disease (n=39) or cardiac amyloidosis (n=79). Various imaging parameters, including late gadolinium enhancement (LGE) patterns and T1 mapping values derived from CMR, E/e’ and global longitudinal strain (GLS) were analyzed. Discrimination scores were calculated using multivariate analysis, with sensitivity and specificity determined for selected parameters. Results: In Fabry patients, LGE patterns predominantly exhibited a subendocardial distribution (66%), whereas amyloidosis patients showed transmural LGE (93%). LV mass index and T1 mapping values were higher (150±20 vs. 90±15 g/m 2 , 1208±104 vs. 822± 210ms both p p<0.001) in cardiac amyloidosis compared to Fabry disease. Echocardiographic parameters demonstrated significantly reduced GLS (-12±2 vs -18±3%, p<0.001), larger LA size (50 ± 5 mm vs. 40 ± 5 mm, p<0.001) and higher E/e' ratio (15 ± 3 vs. 8 ± 2, p<0.001) in cardiac amyloidosis compared to Fabry disease. Multivariate analysis identified LGE patterns and GLS as significant discriminators, and combining both parameters can discriminate Fabry and Amyloidosis with a sensitivity of 80.0%, specificity of 90.0%, and predictive accuracy of 85.0%. Incorporating LA size, LV mass index and E/e’ further improve the predictive accuracy to 92.0%. Conclusions: Cardiac MRI and echocardiography demonstrate promising discriminatory ability in distinguishing Fabry disease from cardiac amyloidosis. GLS emerges as a valuable parameter, reflecting myocardial function and aiding in accurate diagnosis. Integration of these imaging modalities into clinical practice could enhance diagnostic accuracy and guide appropriate management strategies.

Comparative Study of Random Forest and Support Vector Machine for Land Cover Classification and Post-Wildfire Change Detection

The land use land cover (LULC) map is extensively employed for different purposes. Machine learning (ML) algorithms applied in remote sensing (RS) data have been proven effective in image classification, object detection, and semantic segmentation. Previous studies have shown that random forest (RF) and support vector machine (SVM) consistently achieve high accuracy for land classification. Considering the important role of Portugal’s Serra da Estrela Natural Park (PNSE) in biodiversity and nature conversation at an international scale, the availability of timely data on the PNSE for emergency evaluation and periodic assessment is crucial. In this study, the application of RF and SVM classifiers, and object-based (OBIA) and pixel-based (PBIA) approaches, with Sentinel-2A imagery was evaluated using Google Earth Engine (GEE) platform for the land cover classification of a burnt area in the PNSE. This aimed to detect the land cover change and closely observe the burnt area and vegetation recovery after the 2022 wildfire. The combination of RF and OBIA achieved the highest accuracy in all evaluation metrics. At the same time, a comparison with the Normalized Difference Vegetation Index (NDVI) map and Conjunctural Land Occupation Map (COSc) of 2023 year indicated that the SVM and PBIA map resembled the maps better.

The MeerKAT view on Galactic supernova remnants

The integrated radio spectrum of supernova remnants (SNRs) and the spatial variation of the spectral indices across these extended sources are powerful tools for studying the shocks and particle acceleration processes occurring in different SNR regions. Characterization of these processes requires sensitive flux density measurements and high-resolution images, which are not always available due to observing difficulties. We want to show the potentiality of the high-resolution SARAO MeerKAT legacy Galactic Plane Survey (SMGPS) images regarding the morphological and spectral characterization of 29 known galactic SNRs. We used the SMGPS data at $1.284$ GHz coupled with data from the GaLactic and Extragalactic All-sky Murchison Widefield Array (GLEAM) survey ($0.072-0.231$ GHz) to characterize the integrated spectrum of each source and search for spatial spectral variation through analysis of sensitive spectral index maps. We were able to redefine the exact morphology of four SNRs (G024.7-00.6, G051.4+00.7, G348.7+0.3, and G351.9+00.1), distinguishing them from unrelated sources or identifying new emission regions associated with them and never observed before. In many other cases, we identified in the SMGPS images several overlaid with the remnants, and we were able to estimate their spectral contribution through inspection of the spatial variation of the spectral indices across the remnants. The integrated spectral indices show a more uniform distribution with respect to what is obtained by considering the values reported in the literature. We show that new sensitive and high-resolution data are crucial to firmly constraining both the integrated and spatially resolved spectrum of SNRs, especially for the less studied objects of the southern hemisphere. The comparison of our SMGPS-GLEAM spectral index maps with IR, molecular, and gamma -ray images allowed us to investigate the nature of the peculiar remnant regions.

A Multifrequency View of the Radio Phoenix in the A85 Cluster

Radio phoenices are complex and filamentary diffuse radio sources found in both merging and relaxed clusters. The formation of these sources has been proposed to be due to adiabatic compression of old active galactic nucleus plasma in shock waves. Most of the previous spectral studies of these sources have been limited to integrated spectral indices, which were found to be very steep and show a curved spectrum. Here, we have performed a multifrequency investigation of the radio phoenix in the A85 cluster. Owing to the sensitive high-resolution observations, we found some of the finer filamentary structures that had been previously undetected. We produced resolved spectral index maps of the radio phoenix between 323, 700, and 1280 MHz. The orientation of the filaments, as well as the gradient across the spectral index maps, suggest the possible direction of the shock motion from northeast to southwest. The integrated spectrum of the radio phoenix was found to be very steep and curved toward high frequencies. Furthermore, the spectral index of the filaments was found to be less steep compared to the nonfilamentary regions, implying greater energy injection in the filaments. The observed features in the radio phoenix in the A85 cluster seem to be in support of an adiabatic shock compression mechanism.

Exploring El Nino effects on agricultural area using Landsat images analysis: A case study in Bondowoso Regency, Indonesia

El Nino, which hit Indonesia in 2023, poses severe food security threats due to the high dry season with no rainfall and minimal cloud cover and can trigger serious drought problems if it happen for a long time. This study aimed to explore the impact on agricultural land in Bondowoso Regency during El Nino events. The analysis in this study primarily uses land surface temperature (LST) and normalized difference vegetative index (NDVI) map distribution. The Landsat data from USGS are collected and processed to become LST and NDVI distribution maps. Data analysis focused on the agricultural area layers based on data from the Indonesia geospatial portal. Referring to the LST and NDVI map distribution, the notable rise of LST starts in August 2023, and the peak is in October 2023. Around 46% of areas in the Bondowoso regency are detected as hotspot areas, which had LST above 30<sup>o</sup>C in October 2023. El Nino affects the irrigated lands and rain-fed fields more than the plantations. The NDVI alteration data does not show that the Bondowoso Regency is experiencing extraordinary drought due to the short-term impact of El Nino. However, the emergence of numerous areas in the moderate NDVI category warns that stress affecting vegetation is starting to occur. Mitigation plans should be prepared for the long-term impact of El Nino, particularly in the hotspot areas. This study could be a comprehension tool for the government and farmers to prepare mitigation plans.

Smart structural health monitoring (SHM) system for on-board localization of defects in pipes using torsional ultrasonic guided waves

Most reported research for monitoring health of pipelines using ultrasonic guided waves (GW) typically utilize bulky piezoelectric transducer rings and laboratory-grade ultrasonic non-destructive testing (NDT) equipment. Consequently, the translation of these approaches from laboratory settings to field-deployable systems for real-time structural health monitoring (SHM) becomes challenging. In this work, we present an innovative algorithm for damage identification and localization in pipes, implemented on a compact FPGA-based smart GW-SHM system. The custom-designed board, featuring a Xilinx Artix-7 FPGA and front-end electronics, is capable of actuating the PZT thickness shear mode transducers, data acquisition and recording from PZT sensors and generating a damage index (DI) map for localizing the damage on the structure. The algorithm is a variation of the common source method adapted for cylindrical geometry. The utility of the algorithm is demonstrated for detection and localization of defects such as notch and mass loading on a steel pipe, through extensive finite element (FE) method simulations. Experimental results obtained using a C-clamp for applying mass loading on the pipe show good agreement with the FE simulations. The localization error values for experimental data analysed using C code on a processor implemented on the FPGA are consistent with algorithm results generated on a computer running Python code. The system presented in this study is suitable for a wide range of GW-SHM applications, especially in cost-sensitive scenarios that benefit from on-node signal processing over cloud-based solutions.

Multi-hazard, multidimensional disaster risk validation in selangor’s three urban districts, Malaysia

Considering the increasing impact of natural hazard-related disasters in Malaysia, understanding and evaluating integrated disaster risk must consider multi-hazard and multidimensional vulnerability at the local level, particularly in developing industrial nations like Malaysia. Therefore, this study proposes an improved methodology for conducting an integrated disaster risk assessment index (IDRI) mapping to measure disaster risk within local administrative boundaries in Malaysia. In this study, multi-hazard spatial overlapping combined two common hazards in Malaysia, which are floods and landslides. This study used multidimensional vulnerability, which encompasses six dimensions, 16 subdimensions, and 54 indicators. Researchers applied this approach in three urban districts of Selangor, Malaysia: Sepang, Kuala Langat, and Hulu Langat, which are located within the Langat River catchment and consist of 17 subdistricts. Overall, 32.9% of the total study area was found to be at risk, with 4.3% in the very high-risk area. In comparison with the latest flood events in 2021, the IDRI components were highly correlated with disaster impact. In conclusion, the contribution of this study provides a novel perspective on disaster risk assessment by addressing several types of hazards and multidimensional vulnerability, as compared to the previous methodology focusing on a single hazard and a physical vulnerability factor.

Genome-wide association mapping and genomic prediction of water deficit stress tolerance indices in spring bread wheat

Genome-wide association mapping (GWAM) is crucial for identifying the genetic architecture of quantitative traits, such as drought tolerance indices in bread wheat. This study aims to identify Marker-Trait Associations (MTAs) and genes related to drought tolerance indices in wheat. Seven drought tolerance indices were calculated based on grain weight per spike under field drought stress (FDS) and field non-stress (FNS) conditions. These indices included mean productivity (MP), geometric mean productivity (GMP), relative drought index (RDI), stress tolerance index (STI), tolerance index (TOL), stress susceptibility index (SSI), and yield stability index (YSI). Genotyping of the samples was performed using single nucleotide polymorphism (SNP) markers. A total of 96 MTAs were identified for the studied indices and conditions FNS and FDS in this experiment, with a threshold of -log10p ≥ 3.0. These included FNS, FDS, GMP, MP, STI, SSI, RDI, and YSI, with 15, 11, 16, 16, 20, 6, 6, and 6 MTAs, respectively. The MTAs identified for the drought tolerance indices GMP, MP, and STI were located on chromosomes 2 A, 3B, and 6 A, respectively. Moreover, this study identified four genes related to the indices, namely “TraesCS2B02G000100,” “TraesCS3A02G000100,” “TraesCS2B02G000200,” and “TraesCS4B02G000100”. These genes play a crucial role in drought tolerance and can be utilized for marker-assisted selection to enhance drought tolerance wheat genotypes.

Suitability mapping for alternative crops: A consistent, high-resolution approach for the United States

Alternative crops are a key aspect of many nature-based solutions in agriculture, and there is a need for more consistent geographic information on biophysical suitability to aid in both farm-level planning and larger-scale analyses. Here we describe an approach for generating consistent, replicable, high-resolution suitability maps for any alternative crop species across the USA. The method employs a criteria-based approach to map potential species performance using a simple suitability index. Criteria for suitable and ideal ranges of values for influential biophysical variables are created using data collected from published sources and are reviewed by experts. Publicly available soil and climate map data are used with the criteria to map suitability for each variable which are integrated into an overall suitability index map. Maps of unsuitable locations are combined to produce a limiting variable map showing which category of environmental variables is most limiting. We demonstrate the application of this approach for two alternative perennial crops, apple (Malus spp.) and Chinese chestnut (Castanea mollissima) and validate its accuracy using known farm locations. Maps of apple and chestnut in four distant study regions show varying patterns of suitability and potential performance depending on the climate and geophysical characteristics of the region. The maps can be used to identify areas of high suitability and compare across regions or between species and be combined with socio-economic and environmental datasets for further analysis. Compared to other approaches, ours can be applied to multiple species with a range of pre-existing knowledge in a consistent way, allowing for reliable mapping and subsequent research and planning for alternative crops and nature-based solutions in agriculture.

Flood Susceptibility Mapping Using Analytic Hierarchy Process and Geographic Information System in Baitarani Basin of Odisha, India

Baitarani, the 6th largest river basin in Odisha, eastern India, faces water related challenges in its catchments. As one of the most frequent environmental disasters, floods are consistently cited in hotspots of the eastern region in India. Hence, in this study, flood susceptibility maps were generated for Baitarani River basin by using analytical hierarchy process technique and geographic information system. Eleven thematic maps of topographic ruggedness index, topographic wetness index, stream power index, elevation, lithology, soil, slope, drainage density, distance from drainage network, land use/land cover and normalized difference vegetation index were prepared for flood vulnerability mapping. The themes were assigned suitable weights depending on relative influence of each of the themes on flood risk. The results indicated that 87% of the basin falls under intermediate flood susceptibility zone, while 10% is classified under high flood hazard zone. Areas in the lower elevation catchment, particularly those with flat topography near the coastline, were identified as being highly susceptible to flooding. The impacts of severe flooding in the basin are most pronounced in specific blocks in Jajpur district (Jajpur, Dasarathpur, and Korei blocks), Bhadrak district (Dhamnagar and Bhandaripokhari blocks), and Anandapur block in the Keonjhar district of Odisha. Additionally, changes in land use/land cover during 1995-2020 revealed 8% decline in agricultural land and 13.93% increase in fallow land in the area. The outcomes of this research can help researchers, planners and managers in managing natural resources, find locations that could be vulnerable to flooding, and lessen the damage.

Abnormal functional lateralization and cooperation in bipolar disorder are associated with neurotransmitter and cellular profiles

BackgroundHemispheric lateralization and cooperation are essential for efficient brain function, and aberrations in both have been found in psychiatric disorders such as schizophrenia. This study investigated alterations in hemispheric lateralization and cooperation among patients with bipolar disorder (BD) and associations with neurotransmitter and cell-type density distributions to identify potential molecular and cellular pathomechanisms. MethodsSixty-seven BD patients and 127 healthy controls (HCs) were examined by resting-state functional MRI (rs-fMRI). Whole-brain maps of the autonomy index (AI) and connectivity between functionally homotopic voxels (CFH) were constructed to reveal BD-specific changes in brain functional lateralization and interhemispheric cooperation, respectively. Spatial associations of regional AI and CFH abnormalities with neurotransmitter and cell-type density distributions were examined by correlation analyses. ResultsBipolar disorder patients exhibited higher AI values in left superior parietal gyrus, cerebellar right Crus I, and cerebellar right Crus II, and these regional abnormalities were associated with the relative densities (proportions) of oligodendrocyte precursor cells and microglia. Patients also exhibited lower CFH values in right inferior parietal gyrus, bilateral middle occipital gyrus, left postcentral gyrus, and bilateral cerebellar crus II, and these regional abnormalities were associated with the densities of serotonin 1A and dopamine D2 receptors, oligodendrocyte precursor cells, astrocytes, and neurons. ConclusionsThese findings indicate that abnormal functional lateralization and cooperation in BD with potential molecular and cellular basis.

Remote sensing assessment of wildfire using high-resolution PlanetScope satellite observations: A case study on Co Tien Mountain, Nha Trang City, Vietnam

In this study, high spatial resolution (3 m) PlanetScope (PS) imagery was utilized to map burned areas caused by a wildfire occurring on January 10, 2024, on Co Tien Mountain in Nha Trang city, Khanh Hoa province, South Central Coast of Vietnam. A pre-fire image, acquired ten days earlier, on December 31, 2023, and a post-fire one, acquired nearly one month after, on February 04, 2024, were used to create pre- and post-fire Normalized Difference Vegetation Index (NDVI) maps of the study area, then the difference of NDVI (dNDVI). A threshold (T = 0.20), proposed by the author, was applied to the histogram of the dNDVI product to classify the study area into two clusters: burned pixels (dNDVI > T) and unburned pixels (dNDVI <= T). Classification results estimate that a total of 16.11 ha of grass, reeds, small shrubs and vegetation have been burned out during the wildfire. A field trip is required to map the burned areas using unmanned aerial vehicles (UAVs) for an accurate validation of results derived purely from PS satellite observations. Although lacking a ground truth dataset for validation is a significant limitation, the proposed approach remains beneficial for local managers and decision-makers. It enables the rapid assessment of damages caused by small wildfires and provides essential data for effective disaster management and recovery planning, particularly in remote areas.

Spatio-temporal soil loss modelling using RUSLE and sediment delivery into a reservoir in a semi-arid region of northern Nigeria

Soil loss is aggravated by uncontrolled deforestation, indiscriminate land clearing for agricultural activities, overgrazing, and urban development that leads to severe soil erosion over the land surface. The main objective of this research is to apply the Revised Universal Soil Loss Equation (RUSLE), in conjunction with remote sensing and GIS, to determine the temporal variation of soil loss from the Gubi watershed in the years 2000 and 2017 and to estimate the sediment delivery into the Gubi reservoir in Northern Nigeria. Datasets of rainfall, soil type, topography, cover management, and support practice were utilized to determine the five RUSLE factors. The research identified five levels of erosion ranging from severe to very low-risk areas. The spatial distribution of erosion hotspots in the catchment area was highlighted. Results revealed increasing levels of erosion from 14,244.31 tons/year in 2000 to 16,792.33 tons/year in 2017. Consequently, the catchment's sediment yield was 6903.65 tons/year and 9172.71 tons/year corresponding to sediment delivery ratios of 48.46 % and 54.62 % in 2000 and 2017 respectively. The sediment inflow into Gubi reservoir was 747.38 tons/year and 950.76 tons/year corresponding to 10.83 % and 10.37 % of the total sediment yield in 2000 and 2017 respectively. Soil erosion vulnerability index maps were produced and the erosion is expected to increase with time as agricultural activities and deforestation continue to occur. The sediment deposits have the potential to reduce the designed life of the reservoir. Best management practices, such as tree planting, mulching, and contour ridging are recommended for soil conservation. There is a need to assess the reservoir sediment deposits so that measures can be taken to maintain the reservoir operations properly.

Modeling forest canopy structure and developing a stand health index using satellite remote sensing

Biotic and abiotic disturbances modify tree structure and degrade stand health. Accurate geospatial data on stand structure is important for monitoring tree growth, forest health, progression and severity of diseases and pests, and estimating resilience to climate stress. The live crown ratio (LCR) of trees serves as a key health indicator but has been understudied at the landscape level using remote sensing data. This study generated the leaf area index (LAI) and a novel spatial layer of LCR at site and landscape scales using a combination of satellite data and ground observations. We conducted field surveys to collect plot-level (10 m × 10 m) data in four eastern white pine (EWP; Pinus strobus L.)-dominated sites in the state of Maine, USA. The plot-level data were used to develop regression models for LAI and LCR estimation using microwave (Sentinel-1) and optical (Sentinel-2) remote sensing data and applying the Random Forest (RF) and Support Vector Machine (SVM) machine learning algorithms. The RF model showed higher prediction accuracy than the SVM model at the site level. Moreover, the prediction accuracy at the site and landscape levels were comparable for LAI (R2 > 0.76) and LCR (R2 > 0.71) using the RF model. Furthermore, the predicted LAI and LCR were integrated with canopy height and stand density to develop a novel health index map for EWP. The resulting health index map successfully delineated patches representing various health categories. Forestry practitioners and decision-makers can use the derived health index map and intermediate spatial data layers (LAI and LCR) to guide stand management. The developed framework can potentially be applied to other coniferous and broadleaved species for remote sensing-based LCR estimation and forest health assessment upon further studies and verification.

Spatio-Temporal Analysis of Water Hyacinth Density (Eichhornia crassipes) in Lake Rawa Pening 2019 - 2023 Using NDVI Algorithm on Google Earth Engine (GEE)

Abstract Water hyacinth (Eichhornia crassipes) is an aquatic plant that floats in freshwater waters that has the ability to grow very fast and is invasive. This plant is able to reproduce vegetatively and generatively and is able to double its population within two weeks so that it can endanger the ecosystem in the waters. The purpose of this research is to map the distribution pattern, dynamics of changes in vegetation density and changes in water hyacinth area with spatial-temporal techniques using remote sensing technology processed using GEE in Lake Rawa Pening. The satellite image used is Sentinel level-2A with high spatial resolution with a recording time of May 2019 - 2023. This study uses the NDVI method to measure the greenness of vegetation and help identify the density of water hyacinth vegetation. The results of the vegetation density index show that there are five classification for vegetation density levels, and the outcomes of the accuracy test that was conducted range from -0.15 to 0.94. obtained an overall accuracy of 86.6% and a kappa coefficient value of 0.81. These results show that the use of Sentinel 2A imagery can be used for vegetation density index mapping using the NDVI algorithm in GEE with a good level of accuracy and conformity between map and field and the image processing that has been done is appropriate.

Optical orthogonal frequency division multiplexing with differential index modulation

This paper proposes a differential index modulation (DIM) scheme to address the complex channel estimation challenges in optical orthogonal frequency division multiplexing with index modulation (OOFDM-IM). The main idea of the DIM scheme is to design a time-frequency dispersive matrix with unitary characteristics and perform index mapping based on the Lemer code principles. By applying differential operations, the DIM scheme enables decoding at the receiver without requiring channel estimation. The paper provides a detailed explanation of the design principles and theoretical bit error rate (BER) of the proposed scheme. Simulations based on the exponential Weibull atmospheric turbulence channel model are conducted to compare the DIM scheme with the existing OOFDM-IM scheme. Additionally, a carefully designed proof-of-concept experiment is performed to further validate the scheme’s effectiveness and feasibility. Both simulation and experimental results demonstrate that, compared to OOFDM-IM, the proposed scheme can entirely avoid complex channel estimation with a maximum signal-to-noise ratio (SNR) loss of no more than 4 dB, even under various turbulence intensities and higher-order modulation scenarios. This provides a valuable reference for OOFDM-IM in complex environments or where channel estimation is challenging.

From 100 MHz to 10 GHz: Unveiling the spectral evolution of the X-shaped radio galaxy in Abell 3670

Context. X-shaped radio galaxies (XRGs) are characterised by two pairs of misaligned lobes: active lobes hosting radio jets and the wings. None of the formation mechanisms proposed thus far are able to exhaustively reproduce the diverse features observed among XRGs. Emerging evidence has proposed the existence of sub-populations of XRGs forming via different processes. Aims. The brightest cluster galaxy (BCG) in Abell 3670 (A3670) is a dumbbell system hosting the XRG MRC 2011-298. The morphological and spectral properties of this interesting XRG were first characterised based on Karl G. Jansky Very Large Array (JVLA) data at 1–10 GHz. In the present work, we follow up on MRC 2011-298 with the upgraded Giant Metrewave Radio Telescope (uGMRT) at 120–800 MHz to further constrain its properties and origin. Methods. We carried out a detailed spectral analysis sampling different spatial scales. Integrated radio spectra, spectral index maps, radio colour-colour diagrams, and radiative age maps of both the active lobes and prominent wings were employed to test the origin of the source. Results. We confirm a progressive spectral steepening from the lobes to the wings. The maximum radiative age of the source is ~80 Myr, with the wings being older than the lobes by ≳30 Myr in their outermost regions. Conclusions. The observed properties are in line with an abrupt reorientation of the jets by ~90 deg from the direction of the wings to their present position. This formation mechanism is further supported by the comparison with numerical simulations in the literature, which additionally highlight the role of hydrodynamic processes in the evolution of large wings such as those of MRC 2011-298. It is plausible that the coalescence of supermassive black holes could have triggered the spin-flip of the jets. Moreover, we show that the S-shape of the radio jets is likely driven by precession with a period of P ~ 10 Myr.

Survey of non-thermal electrons around supermassive black holes through polarization flips

Abstract Optically thick non-thermal synchrotron sources notably produce linear polarization vectors that are parallel to projected magnetic field lines on the observer’s screen, although they are perpendicular in well-known optically thin cases. To elucidate the complex relationship between the vectors and fields, and to investigate the energy and spatial distribution of non-thermal electrons through the images, we perform polarization radiative transfer calculations at submillimeter wavelengths. Here the calculations are based on semi-analytic force-free jet models with non-thermal electrons with a power-law energy distribution. In the calculated images, we find a $90{^\circ }$-flip of linear polarization vectors at the base of counter-side (receding) jet near a black hole, which occurs because of large optical depths for the synchrotron self-absorption effect. The $90{^\circ }$-flip of LP vectors is also seen on the photon ring at a high frequency, since the optical depth along the rays is large there due to the light bending effect. In addition, we see the flip of the sign of circular polarization components on the counter-jet and photon ring. Furthermore, we show that these polarization flips are synthesized with large values in the spectral index map, and also give rise to outstanding features in the Faraday Rotation Measure map. Since the conditions of flipping depend on the magnetic field strength and configuration and the energy distribution of electrons, we can expect that the polarization flips will provide us with observational evidence for the presence of non-thermal electrons around the black hole, and a clue to the magnetic driving mechanism of plasma jets.

Nutrient Potential Mapping of Soils for Tea Plants Through Laboratory and Geostatistical Approaches

<p>The assessment of nutrient potential is crucial for enhancing tea production and achieving sustainable agricultural goals. Thus, the present study was carried out to assess and map the soil nutrient potential for tea plants through laboratory and geostatistical methods. A total of 74 random soil samples with 3 replications were collected from 0 to 9 cm (topsoil) and 9 to 18 cm (subsoil) depths from Oodaleah Tea Garden (OTG) which belongs to Fatikchhari Upazila of Chattogram District in Bangladesh. All the laboratory analyses were done following standard procedures and maps of individual soil indices were prepared through the Inverse Distance Weighted (IDW) interpolation technique using ArcGIS 10.7 software. The integration of maps for nutrient potential was performed following the Analytic Hierarchy Process (AHP). The mean concentrations of organic matter (OM), total nitrogen (TN), available phosphorus (AvP), available potassium (AvK), and available calcium (AvCa) were found higher at 0 to 9 cm compared to 9 to 18 cm soil depth with significant (<em>p</em> < 0.05) difference among the sampling sites. The maps of individual soil parameters revealed distinct spatial differences at 0 to 9 cm and 9 to 18 cm soil depths. The total study area covered 5.99 km<sup>2</sup>. Integrated nutrient potential mapping showed that moderately suitable (44.15%) accounted for the largest proportion, followed by highly suitable (26.03%), generally suitable (21.67%), marginally suitable (7.06%), and unsuitable area (1.08%) of the tea plantation suitability evaluation. The integrated map of nutrient potential will aid in better management of the tea soils.</p>

Deformation and $K$-theoretic index formulae on boundary groupoids

Motivated by investigating K -theoretic index formulae for boundary groupoids of the form {\mathcal{H}}= M_{0} \times M_{0} \sqcup G \times M_{1} \times M_{1} \rightrightarrows M = M_{0} \sqcup M_{1}, where G is an exponential Lie group, we introduce the notion of a deformation from the pair groupoid , which makes sense for general Lie groupoids. Once there exists a deformation from the pair groupoid for a (general) Lie groupoid {\mathcal{G}}\rightrightarrows M , we are able to construct explicitly a deformation index map relating the analytic index on {\mathcal{G}} and the index on the pair groupoid M \times M , which in turn enables us to establish index formulae for (fully) elliptic (pseudo)differential operators on {\mathcal{H}} by applying the numerical index formula of M. J. Pflaum, H. Posthuma, and X. Tang. In particular, we find that the index is given by the Atiyah–Singer integral but does not involve any \eta -term in the higher codimensional cases. These results recover and generalize our previous results for renormalizable boundary groupoids via renormalized traces.